AbstractEngineering is developing extensive leadership education, supporting future professional engineers to engage with others in solving complex sociotechnical problems. A contemporary challenge is to integrate leadership learning into foundational coursework requirements.
An automated identification and integration method has been developed for in-use vehicle emissions under real-world conditions. This technique was applied to high-time-resolution air pollutant measurements of in-use vehicle emissions performed under real-world conditions at a near-road monitoring station in Toronto, Canada, during four seasons, through month-long campaigns in 2013– 2014. Based on carbon dioxide measurements, over 100 000 vehicle-related plumes were automatically identified and fuel-based emission factors for nitrogen oxides; carbon monoxide; particle number; black carbon; benzene, toluene, ethylbenzene, and xylenes (BTEX); and methanol were determined for each plume. Thus the automated identification enabled the measurement of an unprecedented number of plumes and pollutants over an extended duration. Emission factors for volatile organic compounds were also measured roadside for the first time using a proton transfer reaction time-of-flight mass spectrometer; this instrument provided the time resolution required for the plume capture technique. Mean emission factors were characteristic of the lightduty gasoline-dominated vehicle fleet present at the measurement site, with mean black carbon and particle number emission factors of 35 mg kg fuel−1 and 7.5 × 1014 # kg fuel−1 , respectively. The use of the plume-by-plume analysis enabled isolation of vehicle emissions, and the elucidation of co-emitted pollutants from similar vehicle types, variability of emissions across the fleet, and the relative contribution from heavy emitters. It was found that a small proportion of the fleet (< 25 %) contributed significantly to total fleet emissions: 100, 100, 81, and 77 % for black carbon, carbon monoxide, BTEX, and particle number, respectively. Emission factors of a single pollutant may help classify a vehicle as a high emitter; however, regulatory strategies to more efficiently target multi-pollutant mixtures may be better developed by considering the co-emitted pollutants as well. ; This study was undertaken with financial support of the Government of Canada through the federal Department of the Environment and operational support from the Ontario Ministry of the Environment. Infrastructure support was provided by the Canada Foundation for Innovation and the Ontario Research Fund. Additional instrumentation, associated calibration standards, and analysis support were provided by the National Air Pollution Surveillance Network, Environment Canada. Specific technical support for the PTR-TOF-MS was provided by Stefan Feil from IONICON Analytik. Robert M. Healy's contribution was funded by the Marie Curie Action FP7-PEOPLE-IOF-2011 (project: CHEMBC, no. 299755).
Abstract Oxidative potential (OP) is a toxicologically relevant metric that integrates features like mass concentration and chemical composition of particulate matter (PM). Although it has been extensively explored as a metric for the characterization of environmental particles, this is still an underexplored application in the occupational field. This study aimed to estimate the OP of particles in two occupational settings from a construction trades school. This characterization also includes the comparison between activities, sampling strategies, and size fractions. Particulate mass concentrations (PM4-Personal, PM4-Area, and PM2.5-Area) and number concentrations were measured during three weeks of welding and construction/bricklaying activities. The OP was assessed by the ascorbate assay (OPAA) using a synthetic respiratory tract lining fluid (RTLF), while the oxidative burden (OBAA) was determined by multiplying the OPAA values with PM concentrations. Median (25th–75th percentiles) of PM mass and number concentrations were 900 (672–1730) µg m–3 and 128 000 (78 000–169 000) particles cm–3 for welding, and 432 (345–530) µg m–3 and 2800 (1700–4400) particles cm–3 for construction. Welding particles, especially from the first week of activities, were also associated with higher redox activity (OPAA: 3.3 (2.3–4.6) ρmol min–1 µg–1; OBAA: 1750 (893–4560) ρmol min–1 m–3) compared to the construction site (OPAA: 1.4 (1.0–1.8) ρmol min–1 µg–1; OBAA: 486 (341–695) ρmol min–1 m–3). The OPAA was independent of the sampling strategy or size fraction. However, driven by the higher PM concentrations, the OBAA from personal samples was higher compared to area samples in the welding shop, suggesting an influence of the sampling strategy on PM concentrations and OBAA. These results demonstrate that important levels of OPAA can be found in occupational settings, especially during welding activities. Furthermore, the OBAA found in both workplaces largely exceeded the levels found in environmental studies. Therefore, measures of OP and OB could be further explored as metrics for exposure assessment to occupational PM, as well as for associations with cardiorespiratory outcomes in future occupational epidemiological studies.
The province of Alberta, Canada, is home to three oil sands regions which, combined, contain the third largest deposit of oil in the world. Of these, the Athabasca oil sands region is the largest. As part of Environment and Climate Change Canada's program in support of the Joint Canada-Alberta Implementation Plan for Oil Sands Monitoring program, concentrations of trace elements in PM2. 5 (particulate matter smaller than 2.5 µm in diameter) were measured through two campaigns that involved different methodologies: a long-term filter campaign and a short-term intensive campaign. In the long-term campaign, 24 h filter samples were collected once every 6 days over a 2-year period (December 2010–November 2012) at three air monitoring stations in the regional municipality of Wood Buffalo. For the intensive campaign (August 2013), hourly measurements were made with an online instrument at one air monitoring station; daily filter samples were also collected. The hourly and 24 h filter data were analyzed individually using positive matrix factorization. Seven emission sources of PM2. 5 trace elements were thereby identified: two types of upgrader emissions, soil, haul road dust, biomass burning, and two sources of mixed origin. The upgrader emissions, soil, and haul road dust sources were identified through both the methodologies and both methodologies identified a mixed source, but these exhibited more differences than similarities. The second upgrader emissions and biomass burning sources were only resolved by the hourly and filter methodologies, respectively. The similarity of the receptor modeling results from the two methodologies provided reassurance as to the identity of the sources. Overall, much of the PM2. 5-related trace elements were found to be anthropogenic, or at least to be aerosolized through anthropogenic activities. These emissions may in part explain the previously reported higher levels of trace elements in snow, water, and biota samples collected near the oil sands operations. ; This study was undertaken with the financial and operational support of the Government of Canada through Environment and Climate Change Canada as part of the Joint Canada-Alberta Implementation Plan for Oil Sands Monitoring program. Infrastructure support was provided by the Canada Foundation for Innovation and the Ontario Research Fund (Project: 19606). The authors thank the Wood Buffalo Environmental Association (WBEA) for support in integrated air sampling collection in the Athabasca oil sands region. We would like also to acknowledge the provincial, territorial, and municipal governments as partners of the National Air Pollution Surveillance (NAPS) Program.
Long-range transport of aerosol from lower latitudes to the high Arctic may be a significant contributor to climate forcing in the Arctic. To identify the sources of key contaminants entering the Canadian High Arctic an intensive campaign of snow sampling was completed at Alert, Nunavut, from September 2014 to June 2015. Fresh snow samples collected every few days were analyzed for black carbon, major ions, and metals, and this rich data set provided an opportunity for a temporally refined source apportionment of snow composition via positive matrix factorization (PMF) in conjunction with FLEXPART (FLEXible PARTicle dispersion model) potential emission sensitivity analysis. Seven source factors were identified: sea salt, crustal metals, black carbon, carboxylic acids, nitrate, non-crustal metals, and sulfate. The sea salt and crustal factors showed good agreement with expected composition and primarily northern sources. High loadings of V and Se onto Factor 2, crustal metals, was consistent with expected elemental ratios, implying these metals were not primarily anthropogenic in origin. Factor 3, black carbon, was an acidic factor dominated by black carbon but with some sulfate contribution over the winter-haze season. The lack of K+ associated with this factor, a Eurasian source, and limited known forest fire events coincident with this factor's peak suggested a predominantly anthropogenic combustion source. Factor 4, carboxylic acids, was dominated by formate and acetate with a moderate correlation to available sunlight and an oceanic and North American source. A robust identification of this factor was not possible; however, atmospheric photochemical reactions, ocean microlayer reaction, and biomass burning were explored as potential contributors. Factor 5, nitrate, was an acidic factor dominated by NO3−, with a likely Eurasian source and mid-winter peak. The isolation of NO3− on a separate factor may reflect its complex atmospheric processing, though the associated source region suggests possibly anthropogenic precursors. Factor 6, non-crustal metals, showed heightened loadings of Sb, Pb, and As, and correlation with other metals traditionally associated with industrial activities. Similar to Factor 3 and 5, this factor appeared to be largely Eurasian in origin. Factor 7, sulfate, was dominated by SO42− and MS with a fall peak and high acidity. Coincident volcanic activity and northern source regions may suggest a processed SO2 source of this factor. ; Funding of this study was provided as part of the Network on Climate and Aerosols Research (NETCARE), Natural Science and Engineering Research Council of Canada (NSERC), the government of Ontario through the Ontario Graduate Scholarship (OGS), and Environment and Climate Change Canada. This project would not have been possible without the collaboration of many skilled individuals, including Allan K. Bertram and Sarah Hanna at the University of British Columbia and Catherine Philips-Smith at the University of Toronto.
Rapidly rising temperatures and loss of snow and ice cover have demonstrated the unique vulnerability of the high Arctic to climate change. There are major uncertainties in modelling the chemical depositional and scavenging processes of Arctic snow. To that end, fresh snow samples collected on average every 4 days at Alert, Nunavut, from September 2014 to June 2015 were analyzed for black carbon, major ions, and metals, and their concentrations and fluxes were reported. Comparison with simultaneous measurements of atmospheric aerosol mass loadings yields effective deposition velocities that encompass all processes by which the atmospheric species are transferred to the snow. It is inferred from these values that dry deposition is the dominant removal mechanism for several compounds over the winter while wet deposition increased in importance in the fall and spring, possibly due to enhanced scavenging by mixed-phase clouds. Black carbon aerosol was the least effi- ciently deposited species to the snow. ; Funding of this study was provided as part of the Network on Climate and Aerosols Research (NETCARE), Natural Science and Engineering Research Council of Canada (NSERC), the government of Ontario through the Ontario Graduate Scholarship (OGS), and Environment and Climate Change Canada. This project would not have been possible without the collaboration of many skilled individuals: Richard Leaitch at Environment Canada and Catherine Philips-Smith and Cheol-Heon Jeong at the University of Toronto.
